Book Image

Artificial Intelligence By Example - Second Edition

By : Denis Rothman
Book Image

Artificial Intelligence By Example - Second Edition

By: Denis Rothman

Overview of this book

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.
Table of Contents (23 chapters)
21
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22
Index

Implementing a k-means clustering solution

The dataset requires preprocessing to be converted into a prototype to prove the financial value of the project.

Never implement an ML solution in a corporate environment without knowing how much profit it represents and the cost of getting the job done. Without profit, a company will not survive. ML, like any other investment, must provide a return on investment (ROI). In our case, ML will reduce the cost of transportation in the warehouse by reducing AGV distances.

The vision

The primary goal of an ML project involving bots can be summed up in one sentence: finding profit by optimizing bot activity. Achieving that goal will lead to obtaining a budget for a full-scale project.

The data provided does not contain distances. However, an estimation can be made per location as follows:

distance = (end time – start time)/average speed of a bot

The start location is usually a loading point near a pier...